Video compression system

ABSTRACT

A video compression system processes images captured from a video camera mounted to a vehicle. Vehicle-mounted sensors generate vehicle motion information corresponding to a current state of motion of the vehicle. An optical flow estimation circuit estimates apparent motion of objects within a visual field. A video encoder circuit in communication with the optical flow estimation circuit compresses the video data from the video camera based on the estimated apparent motion.

BACKGROUND OF THE INVENTION

1. Priority Claim

This application claims the benefit of priority from European PatentApplication No. 06 021719.7, filed Oct. 17, 2006, which is incorporatedby reference.

2. Technical Field

This disclosure relates to video systems. In particular, this disclosurerelates to video data compression systems.

3. Related Art

Vehicle video recording systems may require large amounts of storage.Video data may be compressed based on the differences from video frameto video frame in a pixel-oriented manner. However, such compressiontechniques may be computationally expensive and are not robust. Thesecompression techniques may not faithfully predict frame-to-framechanges.

SUMMARY

A video compression system includes a video camera mounted to a vehicle,and vehicle-mounted sensors. The vehicle-mounted sensors generatevehicle motion information corresponding to a current state of motion ofthe vehicle. An optical flow estimation circuit generates an estimatedmotion of objects within a visual field of the video camera. A videoencoder circuit in communication with the optical flow estimationcircuit compresses the video data from the video camera in accordancewith the estimated motion.

Other systems, methods, features, and advantages will be, or willbecome, apparent to one with skill in the art upon examination of thefollowing figures and detailed description. It is intended that all suchadditional systems, methods, features, and advantages be included withinthis description, be within the scope of the invention, and be protectedby the following claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The system may be better understood with reference to the followingdrawings and description. The components in the figures are notnecessarily to scale, emphasis instead being placed upon illustratingthe principles of the invention. Moreover, in the figures,like-referenced numerals designate corresponding parts throughout thedifferent views.

FIG. 1 is video compression system.

FIG. 2 is video encoder circuit.

FIG. 3 is a camera image.

FIG. 4 is a camera image.

FIG. 5 is a vector representation.

FIG. 6 is a vector representation.

FIG. 7 is a motion vector process.

FIG. 8 is a motion vector process.

FIG. 9 is a compression process.

FIG. 10 is video compression system.

FIG. 11 is a motion vector determination representation.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Video data compression processes may reduce the bandwidth and amount ofstorage capacity required for transmitting and storing video data.Compression processes may be based on spatial redundancy and temporalredundancy. Spatial redundancy may relate to similarities betweenneighboring pixels, while temporal redundancy may relate to thesimilarities between consecutive frames. Spatial and temporalcompression processes may reduce the amount of information saved and/orencoded. Statistical coding processes may convert data into a compresseddata stream.

FIG. 1 is a video compression system 100. The video compression system100 may be installed in a vehicle 102. The video compression system 100may include a digital communication bus 104, such as a Controller AreaNetwork (CAN) bus or a FlexRay™ bus. The digital communication bus 104may connect a plurality of sensors 110-119 to a gateway 130.

The video compression system 100 may include multimedia components, suchas a video encoder circuit 140, a video decoder circuit 150, a videodisplay device 154, and a storage device 156. The video encoder circuit140, the video decoder circuit 150, and the storage device 160 maycommunicate over a multimedia bus 166 according to a predeterminedprotocol, such as Media Oriented Systems Transport protocol or FireWire™(IEEE1394) networking protocol. Other protocols may be used inalternative systems. Data may be transferred between the multimedia bus166 and the digital communication bus 104 through the gateway 130. Thegateway 130 may communicate with the multimedia bus 166 and the digitalcommunication bus 104, which may utilize different formats andprotocols, so that sensor data 170 may be delivered to the video encodercircuit 140 without the use of a wiring harness.

A video camera 178 may generate video data or transmit image data to thevideo encoder circuit 140. The video camera 178 may be mounted to thevehicle 102 or in the vehicle in a forward-facing direction to providefront view images for recording and/or displaying on the video displaydevice 154. Front view images may be displayed to the user to create arecord of events, whether the vehicle 102 is in motion or is stopped.Front view images may be useful for accident investigation or lawenforcement.

The video camera 178 may be mounted to the vehicle 102 or in the vehiclein a rearward-facing direction to provide rear view images for recordingand/or display. Rear view images may be displayed to the user to assistwith parking and/or lane changes. Other cameras 178 may be mounted to orin the vehicle 102 and may face other directions. The video compressionsystem 100 may compress and store the video data provided by the cameras178. Alternatively, the video compression system 100 may directlytransmit the images provided by the video camera 178 to the displaydevice 154 unit without compression and/or storage.

The video encoder circuit 140 may receive a video signal 180 from thevideo camera 178 and compress the video signal. The video encodercircuit 140 may receive the sensor data 170 from the plurality ofsensors 110-119 via the digital communication bus 104 and the gateway130. The video encoder circuit 140 may output compressed video data tothe multimedia bus 166 for transmission to the recording device 160 orthe video decoder circuit 150. The video encoder circuit 140 maydetermine the vehicle's current state of motion from the data receivedfrom the sensors 110-119. The video encoder circuit 140 may process thesignals or data received from the sensors 110-119 to increase the rateof motion vector processing.

The plurality of sensors 110-119 may be part of a control system thatcontrols driveability while controlling emissions, or may be part of asupplemental restraint system, a navigation system, or a combination ofin-vehicle sensors in the vehicle 102. The sensor may measure shaftrotation (e.g., such as a tachometer 110), may act as a forwarddirection indicator 111, a rearward direction indicator 112, a distancesensor 113, a velocity sensor 114, a direction sensor (compass) 115, andan angle sensor 116 coupled to the steering wheel. Some of the sensorsmay include equipment also available in the after-market, such as anaccelerometer 117 (linear acceleration, radial acceleration), agyroscope 118, and a GPS receiver 119.

The video decoder circuit 150 may receive compressed video data from thevideo encoder circuit 140 and/or the recording device 160 through themultimedia bus 166. The video decoder circuit 150 may decode thecompressed video data and transmit the decoded video data to a userdisplay device 154. The display device 154 may be an LCD display deviceor monitor, which may provide video images to the user.

The storage device 160 may receive compressed video data from the videoencoder circuit 140 over the multimedia bus 166. The recording device160 may record and store the data on a recording medium 186, such asmagnetic tape, hard disk, or optical disc. The recording device 160 mayretrieve the video data from the recording medium 186 and transmit theretrieved video data to the video decoder circuit 150 over themultimedia bus 166. The recording device 160 may be configured to storeand retrieve prerecorded video data for entertainment purposes, such asmovies from commercially available DVDs or wireless sources.

FIG. 2 is the video encoder circuit 140. The video encoder circuit 140may compress the video data in accordance with an MPEG standard (MotionPicture Experts Group), such as MPEG-2, MPEG-4, and H.264/AVC or otherstandards. This may allow compatibility with commercially availablerecording devices.

Video input data 210 for each video image or frame may be divided into aplurality of video blocks or video segments by a segmentation circuit220. The video encoder circuit 140 may determine motion vectors for eachof the video blocks or segments of a particular video image based on anestimated apparent motion and a location of the video block within thevideo image.

A predictive coding circuit 226 may generate predicted video images 228.A subtraction circuit 232 may subtract the predicted video images 228from each of the segmented blocks of data to provide a prediction error230. The predictive coding circuit 226 may predict a video block basedon previously encoded video blocks stored in a memory 236, and based onmodel parameters 242 provided by a model circuit 244 or motionestimation circuit. The model parameters 242 provided by the modelcircuit 244 may represent an internal model of the image content. Themodel circuit 244 may receive the video input data 210, and may receiveoptical flow data 250 from an optical flow estimation circuit 260.

A data compression circuit 266 may receive the prediction error 230 andapply compression processes to generate compressed video data 268. Thecompression processes may include orthogonal transformation,quantization, and/or variable-length coding.

A local decoder 272 may receive the compressed video data 268 from thedata compression circuit 266 and may “reverse” the operations performedby the data compression circuit and subtraction circuit 232 to provide alocal “reference copy” of the image. The reference copy of the image maybe reconstructed during processing. The model circuit 244 (motionestimation) may generate current or updated the model parameters 242 bycomparing the model to the video input data 210 and by applying theestimated optical flow data 250 from the optical flow estimation circuit260.

The optical flow estimation circuit 260 may include a motionreconstruction circuit 276 that reconstructs the vehicle's current stateof motion based on the sensor data 170, and may generate the estimatedoptical flow data 250 on a block-by-block basis. The estimated opticalflow data 250 may include motion vectors, which may characterize thecurrent state of the vehicle motion, and may indicate the apparentmotion of objects in the video input data 210. The optical flowestimation circuit 260 may determine the apparent motion of objectswithin the camera's visual field based on the vehicle's current state ofmotion and the relevant camera parameters.

The vehicle's current state of motion may be based on the sensor data170, such as velocity, driving direction, linear acceleration, andradial acceleration. If the available sensor information does not fullyreconstruct of the state of motion, velocity and driving direction maybe derived, while other parameters may use default values. Based on thecurrent state of motion of the vehicle 102, the optical flow within thecamera's visual field may be estimated based on geometricalconsiderations, camera frame rate, and actual displacement of objectsper frame.

FIG. 3 is a captured camera image 300. The camera 178 may be mounted ina forward-facing direction, and may be directed to an area ahead of thevehicle 102. Objects in the left-hand portion of the image may appear tomove toward the lower left-hand portion of the image, while objects inthe right-hand portion of the image may appear to move toward the lowerright-hand portion of the image, as indicated by the arrows 310.

FIG. 4 is a captured camera image 400. The camera 178 may be mounted ina rearward-facing direction, and may be directed to the area behind thevehicle 102. The video images may be obtained while the vehicle 102 isfollowing a right-hand curve. The apparent motion of objects in thecaptured images may be different than when the vehicle 102 is travelingin a straight line or a relatively straight line, as indicated by thearrows 410. In particular, the apparent motion of objects in the videoimages may depend on the vehicle speed, direction of travel, and thepath of the vehicle travel. Other parameters, such as camera focallength and viewing direction of the camera may affect the determinationof apparent motion. Such parameters may be fixed and may be known.

The optical flow estimation circuit 260 of FIG. 2 may generate themotion vectors by searching a predefined search range of possible motionvectors. This may permit adaptive processing of a search range of themotion vectors depending on encoding requirements and sensor data 170.In this manner, the video data 180 provided by the camera 178 may becompressed based on a motion estimation and compensation scheme, whichmay reduce computational requirements.

The optical flow estimation circuit 260 may establish the search rangeor the starting values for searching the motion vectors according to theestimated apparent motion. The motion vectors may be derived withoutsearching the entire video image. The optical flow estimation circuit260 may chose the starting value for determining the motion vectors byselecting the appropriate vector of the vector field for each block ofthe video image. The precision of the resulting motion vectors may beimproved using an iterative process that converges to the motionvectors, which may provide an accurate description of the actual vehiclemotion.

The model parameters 242 may be transmitted to the predictive codingcircuit 226 to predict the video frames or images, and may betransmitted to the data compression circuit 266 for inclusion in thecompressed video data 268. The predictive coding circuit 226 may predictvideo frames based on the model parameters 242, which may correspond tothe motion vectors provided by the optical flow estimation circuit 260.This may reduce temporal correlation between consecutive video images.

The optical flow estimation circuit 260 may provide the optical flowinformation 250 for the estimated apparent motion in form of qualitativeinformation, such as a type of flow field (zoom-in or zoom-out),leftward motion, or rightward motion. This information may be used toincrease the data compression rate. The optical flow estimation circuit260 may also provide optical flow information 250 for the estimatedapparent motion in the form of a vector field representation. The motion(e.g. apparent motion) of objects may be described quantitatively usingvector fields depending on the location of the object within the visualfield of the camera. A starting value or search range for determiningthe motion vectors may be set even if the apparent motion of objects inone part of the visual field is different from objects in another part.For example, if the vehicle 102 is backing into a parking place at avelocity “v” of 1 meter per second, a stationary object within sight ofthe camera 178 may also move at velocity of 1 meter per second. If thecamera's frame rate “f” is 25 images per second, then the object'sdisplacement “s” for two consecutive video images may be determined ass=v/f=40 millimeters. Given the camera's viewing direction and focallength, the optical flow information, and thus the apparent motion ofobjects within the video images, may be derived.

The estimated apparent motion of objects within the visual field of thecamera 178 may be derived even if information regarding the currentstate of motion is incomplete. For example, if the angular sensor 116indicates a right-hand curve or turn, objects recorded by aforward-facing camera may appear to move to the left. If a sensor 112attached to the gear shift indicates that the vehicle 102 is moving inreverse, objects recorded by the rearward-facing camera may appear tomove towards the edge of the image (zoom in). Such qualitativeinformation on the optical flow field may be used to increase the videocompression rate.

Reconstruction of the optical flow may be based on sensor informationthat may be indirectly related to the vehicle's state of motion.Ultrasonic or radio-frequency based sensors (radar) 114 may measure thevehicle's velocity, for example, when backing into a parking space. Suchsensors may measure relative velocities of oncoming vehicles. Theinformation provided by these sensors, along with distance information,may be used to increase the accuracy of the estimated optical flow fieldby confirming assumptions on distance and motion of objects within thecamera's visual field.

FIG. 5 is an optical flow vector representation 500 for a block of data.Optical flow vectors 510 may describe the apparent motion of objectsbased on the vehicle's current state of motion. The optical flow vectors510 may correspond to a vehicle 102 traveling in a straight line, andmay represent the optical flow generated by the motion of the camera.

FIG. 6 is an optical flow vector representation 600 for a block of datacorresponding to a vehicle making a turn. Optical flow vectors 610 maycorrespond to a vehicle 102 executing a right-hand curve or turn.

FIG. 7 represents motion vectors of a conventional process. The processmay define a search range 710 centered around a current video block 750of a previous video image. The process may search for a blocktranslation that yields the best match with the current video image.Because a-priori information may not be available for the apparentmotion of image objects 760, the search range is made sufficiently largeso as to cover all possible movements of the object. Therefore, a largenumber of candidate translations may need to be evaluated, which mayresult in a large number of pixel difference computations.

FIG. 8 represents motion vectors determined with the video compressionsystem 100 of FIGS. 1-2. The optical flow estimation circuit 260 mayestimate the optical flow field based on the sensor data 170. Based onthe estimated optical flow vectors 810 corresponding to a current blockof video data 816, the actual apparent motion of objects within theblock of data may be estimated. A search range 820 may be defined basedon the estimated apparent motion (estimated optical flow vectors 810).The actual apparent motion of an image object 830 may only slightlydeviate from the estimate, and the search range may be centered aroundthe estimate. Because the search range may be centered around theestimate 810, a relatively small number of candidate translations may beevaluated, and thus a relatively small number of pixel difference valuesmay be computed. This may reduce computational requirements.

Alternatively, motion vectors may be determined using non-linearoptimization processes, such as gradient based processes. An optimumtranslation may be found by computing a gradient of the sum of absolutepixel differences between the translated block of a previous video imageand the current video image. The translation may be iteratively adjustedbased on the computed gradient until the sum of the absolute pixel isminimized. For iterative processes, the accuracy of the final result andthe speed of convergence may depend on the starting value. An accuratevalue may be based on the estimate of the apparent motion based thesensor data 170, which may reduce the number of processing iterations.

Iterative processing or searching may be avoided if predicted motionvectors are used directly. For example, the model circuit 244 (motionestimation) of FIG. 2 may calibrate the model (the motion vectors) byapplying a process to every predetermined number of video images basedon the video input data 210, and may update the model for the remainingvideo images based on the sensor data 170 only. This may reduce thecomputational load for determining the motion vectors. For example, ifan acceleration sensor indicates that there is no change to thevehicle's state of motion, the set of motion vectors need not be updatedto predict the next video image.

However, the set of motion vectors may be updated if the sensorsindicate a change in the vehicle's state of motion. Linear accelerationor deceleration may translate into a scale factor applied to the motionvectors. Even if changes to the vehicle's state of motion are notcompletely known, the available information may be used to update motionvectors to improved starting points for iterative and/or searchprocesses corresponding to the actual motion vectors.

FIG. 9 is a compression process 900. The sensor information is received(Act 910). The sensor information may be used to reconstruct thevehicle's current state of motion (Act 920). Based on the information onthe vehicle's actual motion and camera parameters, such as cameraviewing direction, focal length, and frame rate, the optical flow fieldmay be estimated (Act 930). The optical flow field may indicate theapparent motion of objects within the camera's visual field. Thisestimated optical flow field may be quantitative (vector fieldrepresentation), or may be qualitative (type of the vector field).

The motion vectors may be determined (Act 940) using the estimatedoptical flow field. The motion vectors may be determined based on thereceived video data (Act 944). The estimated optical flow field may beused as a starting point for iteratively determining the motion vectorsto define a restricted search range or to update previously determinedmotion vectors. A current video image may be predicted (Act 950) basedon the motion vectors. The prediction errors and the motion vectors maythen be encoded (Act 960), and compressed video data may be output (Act970).

The video compression system 100 may not be limited to video encodingprocesses based on motion estimation and compensation. The videocompression system 100 may use other processes for predicting videoimages, such as pattern recognition to recognize and track objects, suchas other vehicles, road markings, traffic signs, and landmarks.

The logic, circuitry, and processing described above may be encoded in acomputer-readable medium such as a CD/ROM, disk, flash memory, RAM orROM, an electromagnetic signal, or other machine-readable medium asinstructions for execution by a processor. Alternatively oradditionally, the logic may be implemented as analog or digital logicusing hardware, such as one or more integrated circuits (includingamplifiers, adders, delays, and filters), or one or more processorsexecuting amplification, adding, delaying, and filtering instructions;or in software in an application programming interface (API) or in aDynamic Link Library (DLL), functions available in a shared memory ordefined as local or remote procedure calls; or as a combination ofhardware and software.

FIG. 10 is a model-based video encoder circuit 1002. The model-basedvideo encoder circuit 1002 may be similar to the video encoder circuit140 of FIG. 2, but may omit the optical flow estimation circuit 260 ofFIG. 2. The model circuit 244 (motion estimation) may maintain a modelof the video input data 210. The model generated by the model circuit244 may be used by the predictive coding circuit 226 to generate thepredicted video blocks 228. The model of the input data may not bestatic, and its parameters may be updated by the model circuit 244 basedon the video input data 210. The model circuit 244 may provide the modelparameters 242 to the data compression circuit 266 to be included intothe compressed video data 268. This may permit the local decoder circuit272 to decode compressed video data 268.

FIG. 11 is a motion vector determination representation 1100. Panel Arepresents a previous video image 1110, and panel B represents a currentvideo image 1120. An object 1130 in the current video image 1120 mayhave moved relative to its position in the previous video image 1110. Todetermine the corresponding motion vector, a block 1150 of the previousvideo image may be shifted and compared to the content of the currentvideo image. The shifted position that yields the best match with thecurrent video image may be used to define a motion vector 1160 for thedata block.

The systems may include additional or different logic and may beimplemented in many different ways. A processor or controller may beimplemented as a microprocessor, microcontroller, application specificintegrated circuit (ASIC), discrete logic, or a combination of othertypes of circuits or logic. Similarly, memories may be DRAM, SRAM,Flash, or other types of memory. Parameters (e.g., conditions andthresholds) and other data structures may be separately stored andmanaged, may be incorporated into a single memory or database, or may belogically and physically organized in many different ways. Programs andinstruction sets may be parts of a single program, separate programs, ordistributed across several memories and processors. The systems may beincluded in a wide variety of electronic devices, including a cellularphone, a headset, a hands-free set, a speakerphone, communicationinterface, or an infotainment system.

While various embodiments of the invention have been described, it willbe apparent to those of ordinary skill in the art that many moreembodiments and implementations are possible within the scope of theinvention. Accordingly, the invention is not to be restricted except inlight of the attached claims and their equivalents.

1. A video compression system comprising: a video camera mounted to orin a vehicle, and configured to generate video data; at least one sensorconfigured to generate vehicle motion information corresponding to acurrent state of motion of the vehicle; an optical flow estimationcircuit configured to generate an estimated apparent motion of objectswithin a visual field of the video camera, where the optical flowestimation circuit chooses a starting value for determining the motionvectors by selecting an appropriate vector of a vector field for eachblock of the video image associated with the current state of motion ofthe vehicle; a video encoder circuit in communication with the opticalflow estimation circuit, and configured to compress the video data inaccordance with the estimated apparent motion of objects; where theoptical flow estimation circuit further comprises: a motionreconstruction circuit configured to reconstruct the current state ofmotion of the vehicle, wherein the reconstruction is based on thevehicle motion information provided by the at least one sensor; andwherein the estimated apparent motion of objects is determined inaccordance with the reconstructed state of motion of the vehicle.
 2. Thesystem of claim 1, where the estimated apparent motion of objectsincludes qualitative information indicating a type of flow field.
 3. Thesystem of claim 1, where the estimated apparent motion of objectsincludes a vector field representation.
 4. The system of claim 1, wherethe video encoder circuit comprises: a model circuit configured togenerate motion vectors indicating motion within the video data, themotion vectors determined based on the estimated apparent motion ofobjects; and a predictive coding circuit configured generate predictedvideo data based on the motion vectors, and configured to determinedifferences between the video data and predicted video data.
 5. Thesystem of claim 4, where the model circuit generates the motion vectorsby searching a predefined search range of possible motion vectors. 6.The system of claim 5, where the model circuit determines a search rangebased on the estimated apparent motion of objects.
 7. The system ofclaim 5, where the model circuit determines a starting value forsearching the motion vectors based on the estimated apparent motion ofobjects.
 8. The system of claim 4, where the video encoder circuitcomprises a segmentation circuit configured to partition video imagesinto blocks, and where the model circuit determines motion vectors foreach block based on the estimated apparent motion of objects and alocation of the block within the video image.
 9. The system of claim 1,where the video encoder circuit compresses the video data according toan MPEG (Motion Picture Experts Group) format.
 10. The system of claim1, where the at least one sensor comprises a tachometer, anaccelerometer, an angular sensor, a distance sensor, a gyroscope, acompass, or a GPS receiver.
 11. The system of claim 1, where the vehiclemotion information includes velocity, direction of motion, linearacceleration, or radial acceleration.
 12. The system of claim 1, furthercomprising a digital communication bus to facilitate communicationbetween the sensors and the video encoder circuit.
 13. The system ofclaim 12, comprising: a video decoder configured to decode thecompressed video information; and a display device in communication withthe decoder, where the display device is configured to display thedecoded compressed video data.
 14. The system of claim 12, comprising arecording device in communication with the video encoder circuit throughthe communication bus, where the recording device is configured to storethe compressed video data.
 15. A video compression system in or on avehicle, comprising: a video camera mounted to or in the vehicle, thecamera configured to generate video data; at least one sensor configuredto generate vehicle motion information corresponding to a current stateof motion of the vehicle; an optical flow estimation circuit configuredto generate an estimated apparent motion of objects within a visualfield of the video camera, where the optical flow estimation circuitchooses a starting value for determining the motion vectors by selectingan appropriate vector of a vector field for each block of the videoimage associated with the current state of motion of the vehicle; wherethe optical flow estimation circuit further comprises: a motionreconstruction circuit configured to reconstruct the current state ofmotion of the vehicle, wherein the reconstruction is based on thevehicle motion information provided by the at least one sensor; andwherein the estimated apparent motion of objects is determined inaccordance with the reconstructed state of motion of the vehicle; avideo encoder circuit in communication with the optical flow estimationcircuit, and configured to compress the video data in accordance withthe estimated apparent motion of objects; and the video encoder circuitfurther comprising: a model circuit configured to generate motionvectors indicating motion within the video data, the motion vectorsdetermined based on the estimated apparent motion of objects; and apredictive coding circuit configured generate predicted video data basedon the motion vectors, and configured to determine differences betweenthe video data and predicted video data.
 16. A method for compressingvideo data generated by a video camera mounted in or on a vehicle, themethod comprising: generating, by the video camera, video data;generating, by at least one sensor, vehicle motion informationcorresponding to a current state of motion of the vehicle; estimating,by an optical flow estimation circuit, an apparent motion of objectswithin a visual field of the video camera, wherein the optical flowestimation circuit chooses a starting value for determining the motionvectors by selecting an appropriate vector of a vector field for eachblock of the video image associated with the current state of motion ofthe vehicle; and compressing, by a video encoder circuit, the video datain accordance with the estimated apparent motion of objects, wherein thevideo encoder circuit is communicating with the optical flow estimationcircuit; reconstructing, by a motion reconstruction circuit of theoptical flow estimation circuit, the current state of motion of thevehicle based on the sensor data; wherein estimating the apparent motionof objects is based on the reconstructed current state of motion of thevehicle.
 17. The method of claim 16, where estimating the apparentmotion of objects generates qualitative information indicating a type offlow field.
 18. The method of claim 16, where estimating the apparentmotion of objects generates vector field representation information. 19.The method of claim 16 comprising: determining motion vectors indicativeof motion within a subsequent video image, the motion vectors determinedbased on the estimated apparent motion of objects within the visualfield of the camera; and predictively coding differences between thevideo data and video images predicted from the motion vectors.
 20. Themethod of claim 19, comprising determining the motion vectors bysearching a predefined search range of possible motion vectors.
 21. Themethod of claim 20, comprising determining the motion vectors byestablishing a search range in accordance with the estimated apparentmotion of objects.
 22. The method of claim 20, comprising: segmenting avideo image into a plurality of data blocks; and determining motionvectors for each block in accordance with the estimated apparent motionof objects and a location of the block within the video image.